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17th Women in Machine Learning Workshop (WiML 2022) 17th Women in Machine Learning Workshop (WiML 2022) The Workshop is co-located with NeurIPS on Monday, November 28th, 2022 at the New Orleans Convention Center in Louisiana, USA. Speakers Logistics Program Call for Participation Committee FAQ Machine learning is one of the fastest growing areas of computer science research. Search engines, text mining, social media analytics, face recognition, DNA sequence analysis, speech and handwriting recognition, healthcare analytics are just some of the applications in which machine learning is routinely used. In spite of the wide reach of machine learning and the variety of theory and applications, it covers, the percentage of female researchers is lower than in many other areas of computer science. Most women working in machine learning rarely get the chance to interact with other female researchers, making it easy to feel isolated and hard to find role models. The annual Women in Machine Learning Un-Workshop is the flagship event in un-conference style of Women in Machine Learning , primarily intended to foster active participant engagement in the program. This technical workshop gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, network and exchange ideas, participate in career-focused panel discussions with senior women in industry and academia and learn from each other. Underrepresented minorities and undergraduates interested in machine learning research are encouraged to attend. We welcome all genders; however, any formal presentations, i.e. talks and posters, are given by women. We strive to create an atmosphere in which participants feel comfortable to engage in technical and career-related conversations. Now in its 4th year, the 2023 un-workshop is co-located with IC ML . Besides this annual un-workshop, Women in Machine Learning also organizes annual workshop at NeurIPS, events such as lunch or social at the AISTATS or AAAI conferences, maintains a public directory of women active in ML, profiles the research of women in ML, and maintains a list of resources for women working in ML. All participants are required to abide by the WiML Code of Conduct . I'm a paragraph. Click here to add your own text and edit me. It's easy. Invited Speakers Location Type of registration required to attend PROGRAM PANELISTS BREAKOUT SESSIONS COFFEE MEET & MINGLE SOCIAL Program Monday, November 28, 2022 [ in-person ] ( Time in CT) Morning Session 7:30 am - 8:30 am Registration & Breakfast 8:30 am - 8:45 am Opening Remarks - Konstantina Palla (Senior Program Chair) 8:45 am - 9:00 am D&I Chair remarks - Danielle Belgrave 9:00 am - 9:10 am Contributed talk ( Tejaswi Kasarla ) - "Maximum Class Separation as Inductive Bias in One Matrix" 9:10 am - 9:20 am Contributed talk ( Taiwo Kolajo ) - "Pre-processing of Social Media Feeds based on Integrated Local Knowledge Base" 9:20 am - 9:55 am Invited talk - Alice Oh - " The importance of multiple languages and multiple cultures in NLP research " 9:55 am - 10:10 am Coffee break 10:10 am - 10:25 am WiML Board Remarks - Jessica Schrouff 10:25 am - 11:00 am Invited talk - Raesetje Sefala - " Constructing visual datasets to answer research questions " 11:00 am - 11:10 am Contributed talk ( Pascale Gourdeau ) - "When are Local Queries Useful for Robust Learning?" 11:10 am - 11:20 am Contributed talk ( Annie S Chen ) - "You Only Live Once: Single-Life Reinforcement Learning" 11:20 am - 1:20 pm Mentorship roundtables & Lunch - Mentors: Adam Roberts, Stephanie Hyland, Bianca Zadrozny, Sima Behpour, Mercy Asiedu, Franziska Boenisch, Eleni Triantafillou, Isabela Albuquerque, Yisong Yue, Amy Zhang, Zelda Mariet, Tristan Naumann, Danielle Belgrave, Shakir Mohamed, Tong Sun, Gintare Karolina Dziugaite, Samy Bengio, Rianne van den Berg, Maja Rudolph, Luisa Cutillo, Ioana Bica, Clara Hu, Rosanne Liu, Jennifer Wei, Alice Oh, SueYeon Chung, Erin Grant, Sasha Luccioni, Michela Paganini, Mounia Lalmas-Roelke, Claire Vernade, Alekh Agarwal, Neema Mduma, Vinod Prabhakaran, Savannah Thais, Jonathan Frankle, Ce Zhang, Rose Yu, Jessica Schrouff, Bo Li, Katherine Heller, Ben Poole, Setareh Ariafar, Christina Pavlopoulou, Isabel Morlidge, Kavya Srinet, Cheng Zhang, Elise van der Pol, Diana Montanes, Lise Diagne, Le Yu, Megan Forrester. Afternoon Session 1:20 pm - 1:55 pm Invited talk - Bianca Zadrozny - " Machine Learning for Climate Risk " 1:55 pm - 2:05 pm Contributed talk ( Elizabeth Bondi-Kelly ) - "Human-AI Interaction in Selective Prediction Systems" 2:05 pm - 2:15 pm Contributed talk ( Gowthami Somepalli ) - "Investigating Reproducibility from the Decision Boundary Perspective." 2:15 pm - 2:35 pm Coffee break 2:35 pm - 3:10 pm Invited talk - Hima Lakkaraju - " A Brief History of Explainable AI: From Simple Rules to Large Pretrained Models " 3:10 pm - 4:10 pm Panel discussion 4:10 pm - 4:20 pm Closing Remarks 4:20 pm - 4:30 pm Poster setup 4:30 pm - 6:00 pm Joint Affinity Groups Poster Session Mentorship Roundtables AI and Creativity: Adam Roberts (Google Brain) Choosing between Academia and Industry: Stephanie Hyland (Microsoft Research) and Bianca Zadrozny (IBM Research) Continual Learning & Open-World Learning: Sima Behpour (Bosch) Founding and Funding Startups: Mercy Asiedu (Google) Gender-related challenges: Franziska Boenisch (Vector Institute) Generalization & Robustness: Eleni Triantafillou (Google Brain) and Isabela Albuquerque (DeepMind) Getting a job (academia): Yisong Yue (Caltech) and Amy Zhang (UT Austin) Getting a job (industry): Zelda Mariet (Google) Healthcare/clinical applications: Danielle Belgrave (DeepMind) and Tristan Naumann (Microsoft Research) Leadership: Shakir Mohamed (DeepMind) and Tong Sun (Adobe) Learning theory: Karolina Dziguaite (Google Brain) Life in industry research: Samy Bengio (Apple) and Rianne van den Berg (Microsoft Research) Life with kids: Maja Rudolph (BCAI) and Luisa Cutillo (University of Leeds) Mental health & surviving in grad school: Ioana Bica (DeepMind), Clara Hu (Google Brain), and Rosanne Liu (Google Brain) ML for Science: Jennifer Wei (Google) Natural language processing: Alice Oh (KAIST) Negotations in ML: Nicole Bannon (81cents) Neuroscience & cognitive science: Erin Grant (UCL), SueYeon Chung (NYU/Flatiron Institute), and Noga Zaslavsky Non-traditional paths in machine learning: Sasha Luccioni (HuggingFace) and Michela Paganini (DeepMind) Recommender systems: Mounia Lalmas-Roelke (Spotify) Reinforcement learning: Claire Vernade (DeepMind), Alekh Agarwal (Google), and Elise van der Pol (Microsoft Research) Seeking funding in academia: Neema Mduma (The Nelson Mandela African Institution of Science and Technology) Social science applications: Vinod Prabhakaran (Google Research), Savannah Thais (Columbia University), and Sarah Brown (University of Rhode Island) Systems and machine learning: Jonathan Frankle (Harvard University/MosaicML) and Ce Zhang (ETH Zurich) Time Series: Rose Yu (UCSD) Trustworthy machine learning: Jessica Schrouff (DeepMind), Bo Li (UIUC), and Katherine Heller (Google Research) Monday, December 5, 2022 [virtual](Time in ET) 9:30 am - 9:40 am Opening Remarks 9:40 am - 9:55 am Contributed talk ( Okechinyere J Achilonu ) - "Natural language processing for automated information extraction of cancer parameters from free-text pathology reports" 9:55 am - 10:10 am Contributed talk ( Paula Harder ) - "Physics-Constrained Deep Learning for Climate Downscaling" 10:10 am - 10:25 am Contributed talk ( Silvia Tulli ) - "Explanation-Guided Learning for Human-AI collaboration" 10:25 am - 10:40 am Contributed talk ( Mina Ghadimi Atigh ) - "Hyperbolic Image Segmentation" 10:40 am - 10:50 am Set up (for mentorship session) 10:50 am - 11:50 am Mentorship Panel (Discussion + Q&A) withJenn Wortman Vaughan (Microsoft Research),Colin Raffel (University of North Carolina)Kristen Grauman (University of Texas at Austin) 11:50 am - 12:00 pm Break 12:00 pm - 12:35 pm Sponsor Talks 2:00 pm - 4:00 pm Joint Affinity Groups Poster Session Call for Participation PLATINUM SPONSORS PLATINUM SPONSORS PLATINUM SPONSORS Committee ORGANIZERS WiML RECEPTION ORGANIZER ADVISORY SUPER VOLUNTEERS FAQs

All events WiML Partner Event: New England Women in ML Event with IBM Research Cambridge, Massachusetts April 19, 2019 03:45 pm — 06:00 pm WiML is excited to announce an event by WiML Partner IBM Research in the Cambridge area. The goal is to encourage and support local women, especially students, post-docs, early career researchers and engineers, by offering seminars from thought-leading women in ML, providing opportunities to present their own research, and connecting them to mentors, role models and colleagues. Join the event this Thurs 6/20. Speakers and activities include: – A talk by Tamara Broderick (Assistant Professor, MIT) on “Approximate Cross Validation for Large Data and High Dimensions”. – Reception immediately after the event. When: Thursday June 20, 2019, 4:00pm – 5:00pm with reception immediately after the event Where: IBM Research Cafe, 75 Binney St. Cambridge, MA Organized by IBM Research. Questions? Contact Preethi Raghavan at praghav@us.ibm.com . Thanks to the organizers Lisa Amini (IBM Research), Preethi Raghavan (IBM Research), Kristen Severson (IBM Research). IBM Research is a WiML Platinum Partner. Previous Next

All events WiML Breakfast @ AAAI 2016 Phoenix, Arizona February 15, 2016 07:45 am — 08:45 am WiML is co-hosting a breakfast at AAAI 2016 in Phoenix, Arizona, “Breakfast with Champions: A Women’s Mentoring Event”. In this event, women students will get the opportunity to meet senior women in computer science and/or artificial intelligence. The organizers are: Amy McGovern, Kiri Wagstaff, Sarah Brown, and Marzyeh Ghassemi. The event is also sponsored by AI Journal. Date: Wednesday, 15 February 2016, 07:45-08:45 Venue: Remington, 2nd Floor, Hyatt Regency Phoenix Hotel Event details: http://www.aaai.org/Conferences/AAAI/2016/aaai16student.php Registration: Register during AAAI registration ( http://www.aaai.org/Conferences/AAAI/aaai16.php ) If you see any errors or omissions or have any information to contribute to this page, please contact us at info@wimlworkshop.org SPONSORS Previous Next

All events 3rd WiML Mentorship Program for PhD Applications: Panel on Research Statements Virtual October 23, 2023 4:00 pm - 5:00 pm This event, part of the WiML’s 2023-2024 Mentorship Program on the theme of PhD applications, takes place 4-5pm UTC in Zoom. Mentors and mentees of the 2023-2024 Mentorship Program are invited to attend. The panel topic is on “How to write a research statement for Master’s & Ph.D applications in ML”. Panelists: Emma Pierson (Cornell Tech), Sinead Williamson (UT Austin) Moderator: Erin Grant (UC Berkeley) Previous Next

All events WiML Workshop 2015 Montreal, Canada December 7, 2015 07:30 am — 06:00 pm The 10th annual Women in Machine Learning workshop will be colocated with NIPS 2015 in Montreal, Canada in December 2015. See the workshop website for details! The organizers are: Abbie Jacobs, Kate Niehaus, Svitlana Volkova, Maithra Raghu, and Ramya Ramakrishnan. The invited speakers are: Raia Hadsell, Lillian Lee, Been Kim, and Corinna Cortes, with Amy Greenwald, Hanna Wallach, and Jennifer Wortman Vaughan giving the opening remarks. Previous Next

All events WiML Workshop 2012 Lake Tahoe, Nevada December 3, 2012 08:00 am — 06:00 pm The 7th annual Women in Machine Learning workshop was colocated with NIPS 2012 in Lake Tahoe, Nevada in December 2012. The workshop website is no longer maintained. The organizers were: Tamara Broderick, Minmin Chen, Pallika Kanani, and Tejaswini Narayanan, with faculty advisor Raquel Urtasun. If you see any errors or omissions or have any information to contribute to this page, please contact us at info@wimlworkshop.org Previous Next

All events WiML Workshop 2019 Vancouver, Canada December 9, 2019 08:00 am — 06:00 pm The 14th annual Women in Machine Learning workshop will be colocated with NeurIPS 2019 in Vancouver, Canada in December 2019. See the workshop website for details! The organizers are: Michela Paganini, Sarah Aerni, Forough Poursabzi Sangdeh, Nezihe Merve Gürel, and Bahare Fatemi. Previous Next

All events 2nd WiML Mentoring Program for PhD Applications: Panel on Essay Writing Virtual October 6, 2022 9:00 am - 10:00 am This event, part of the WiML’s 2022-2023 Mentorship Program on the theme of PhD applications, takes place 9-10am PT in Zoom. Mentors and mentees of the 2022-2023 Mentorship Program are invited to attend. Panelists: Sinead Williamson (University of Texas Austin), Mihaela van der Schaar (University of Cambridge), Sanmi Koyejo (University of Illinois Urbana-Champaign; Stanford University), Awa Dieng (Mila) Moderator: Kristy Choi (Stanford University) Previous Next

All events WiML Social @ ICLR 2023 Kigali, Rwanda May 3, 2023 3:00 pm - 5:00 pm Date: May 3, 2023 Time: 3:00-5:00pm Loc: Larder Terrace (in the Hotel of the conference center) The topic of the panel will be AI moving forward, leaving no one behind . We hope to get a conversation going regarding ChatGPT, international collaborations, copyright issues of foundational models etc. The program is: 3:00 pm - 3.45 pm Introduction and networking 3.45 pm - 4.30 pm panel discussion on “AI moving forward, leaving no one behind” 4.30 pm – 5:00 pm Networking roundtables Panelist Bios Panelist: Tegan Maharaj Tegan is an Assistant Professor in the Faculty of Information at the University of Toronto, an affiliate of the Vector Institute and Schwartz-Reisman Institute for Technology and Society, and a visiting researcher at the Centre for the Study of Existential Risk at Cambridge University. She is also a managing editor at the Journal of Machine Learning Research (JMLR), the top scholarly journal in machine learning, and co-founding member of Climate Change AI (CCAI), an organization which catalyzes impactful work applying machine learning to problems of climate change. Prior to joining the iSchool, Tegan did her Ph.D. at Mila and Polytechnique Montreal, where she was an NSERC and IVADO-awarded scholar with Chris Pal. Her recent research has two themes (1) Real-world generalization, learning theory, and practical auditing tools (e.g. unit tests, sandboxes) to empirically evaluate learning behavior or simulate deployment of an AI system (2) Deep representation learning & predictive methods in ecological dynamical systems for impact assessment, policy analysis, and risk mitigation, especially for climate and common-good problems. Panelist: Kathleen Siminyu Kathleen Siminyu is an AI Researcher focused on Natural Language Processing(NLP) for African Languages. She works at Mozilla Foundation as a Machine Learning Fellow to support the development of a Kiswahili Speech Recognition dataset and to build transcription models for end use cases in the agricultural and financial domains. In this role, she is keen to ensure the diversity of Kiswahili speakers, in terms of age, gender, accent and language variant/dialect, is catered for in the dataset and models created. She would welcome opportunities exploring the application of speech technologies in education. Kathleen is also currently part of a committee constituted by the African Union to develop an Artificial Intelligence continental strategy for Africa. Before joining Mozilla, Kathleen was Regional Coordinator of AI4D Africa , where she worked with ML and AI communities in Africa to run research programs. One of these, a fellowship for African language dataset creation, led to the creation of over 9 African language datasets. For this work, Kathleen was listed as one of the MIT Technology Review 35 Innovators under 35 for 2022 . She has vast experience as a community organiser having co-organised the Nairobi Women in Machine Learning and Data Science community for three years and she continues to organise as part of the committees of the Deep Learning Indaba and the Masakhane Research Foundation . Supervolunteer: Hewitt Tusiime Hewitt Tusiime is a research assistant at the Makerere Artificial Intelligence Research lab at Makerere University with a particular interest in data science for finance and AI governance and ethics. She graduated from Makerere University with a Bachelor of Science in Software Engineering. She has worked on several research projects related to the application of machine learning algorithms in agriculture, natural language processing, and finance. She also has extensive experience designing and developing protocols for system deployment, ensuring effectiveness, and a smooth user adoption process. She is passionate about the ethical and social implications of AI on different groups of people. She also oversees community engagement while working to achieve research project objectives and strengthen bonds of trust between communities and the project teams. Organiser: Caroline Weis Dr. Caroline Weis is currently an AI/ML Engineer at GSK.ai , working on clinical machine learning applications. Centered around multi-omics and multimodal clinical data, her projects leverage approaches from biomarker discovery, model interpretability and personalised healthcare. Caroline joined GSK.ai after obtaining a PhD in Machine Learning for Healthcare from ETH Zurich, where she developed early clinical machine learning applications for antimicrobial resistance prediction, through developing new kernel methods, adversarial domain adaptation and representation learning. Her research was elected for the Remarkable Outputs award of 2021 by the Swiss Institute of Bioinformatics. Prior to that, she has built an academic background bridging microbiology, biomathematics, and biophysics. She worked on protein X-ray scattering at Lawrence Berkeley National Laboratory and gained experience developing machine learning applications for screening images at Genedata in Basel. She holds an MSc in Biotechnology and a BSc in Integrated Life Sciences. Previous Next

All events WiML Partner Event: Virtual Women in Science Fireside Chat with Amazon Virtual December 9, 2020 11:00 am - 12:30 pm WiML is excited to announce the Virtual Women in Science Fireside Chat by WiML Partner Amazon. Join some of Amazon’s top leaders and researchers in Machine Learning to learn about the valuable knowledge and experience of successful Women in Research at Amazon. These remarkable leaders from Alexa, Consumer and AWS will engage in a casual discussion on innovation, their career path and a Q&A. They are: Na Zhang, ML Science Manager, Customer Trust & Partner Support Vanessa Murdock, Manager Applied Science, Alexa Shopping Nashlie Sephus, Applied Science Manager, Rekognition and Video Katrin Kirchhoff, Senior Manager, Applied Science AWS Transcribe Priya Ponnapalli, Senior Manager, Data Science, AWS ML Solutions Lab These women will share their insights and experiences as women in science and will be covering topics such as navigating your career path, finding a mentor and work life balance. When: Wednesday, December 9th, 2020, 11am – 12.30pm PT Where: Virtual Registration: https://register.gotowebinar.com/register/4812705742642619918 Organized by Amazon. Amazon is a WiML Diamond Partner. Previous Next

All events WiML Mentorship Session @ KDD 2022 Washington DC August 15, 2022 3:30 pm - 5:00 pm The WiML Mentorship Session as part of the WOMEN IN KDD: TOWARDS GENDER EQUITY IN TECH WORKSHOP is happening on Monday, August 15th, 2022, in person as part of the SIGKDD 2022 conference in Washington, DC. The program will include a 90 minute mentorship roundtable session, taking place 3:30 to 5:00 pm EDT. For more information, please navigate to the session booklet here. Previous Next

All events WiML Luncheon @ COLT 2018 Stockholm, Sweden July 9, 2018 12:00 pm — 02:00 pm WiML is hosting a luncheon at COLT 2018 in Stockholm, Sweden. The organizer is Kamalika Chaudhuri. Date: Monday, July 9, 2018, 12pm-2pm Venue: KTH Campus, Stockholm Registration: Register during COLT registration ( www.learningtheory.org/colt2018/ ). If you registered for COLT but did not register for the WiML lunch, check if you can amend your registration to add WiML lunch registration. If not, email Kamalika Chaudhuri (kamalika AT cs DOT ucsd DOT edu) to attend the lunch. If you are not attending COLT but wish to attend the lunch, also email Kamalika. If you see any errors or omissions or have any information to contribute to this page, please contact us at info@wimlworkshop.org SPONSORS -Platinum- -Diamomd- Previous Next